Log Energy Entropy-Based EEG Classification with Multilayer Neural Networks in Seizure

@article{Aydn2009LogEE,
  title={Log Energy Entropy-Based EEG Classification with Multilayer Neural Networks in Seizure},
  author={Serap Aydın and Hamdi Melih Saraoglu and Sadik Kara},
  journal={Annals of Biomedical Engineering},
  year={2009},
  volume={37},
  pages={2626-2630}
}
In this study, normal EEG series recorded from healthy volunteers and epileptic EEG series recorded from patients within and without seizure are classified by using Multilayer Neural Network (MLNN) architectures with respect to several time domain entropy measures such as Shannon Entropy (ShanEn), Log Energy Entropy (LogEn), and Sample Entropy (Sampen). In tests, the MLNN is performed with several numbers of neurons for both one hidden layer and two hidden layers. The results show that segments… CONTINUE READING
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Quantitative discrimination of the binary gas mixtures using a combinational structure of the probabilistic and multilayer neural networks

  • A. Gulbag, F. Temurtas, I. Yusubov
  • Sens . Actuat . B Chem .
  • 2008

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